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                        Jupyter-notebook拓展应用
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                        包和环境管理器：conda
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                        pip和Virtualenv
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                        标记语言：Markdown
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                        Markdown语法
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                        文档管理工具-Gitbook
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                            <b>3.</b>
                        
                        数据分析库-Pandas
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                            <b>3.1.</b>
                        
                        pandas
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                            <b>3.2.</b>
                        
                        Series
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                            <b>3.3.</b>
                        
                        DataFrame对象-创建
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                        DataFrame查询1-整体
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                        DataFrame查询2-专用查询
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                        DataFrame查询3-专有查询：过滤查询
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                            <b>4.4.</b>
                        
                        Pandas对象的数据操作：增删改查
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                            <b>4.4.1.</b>
                        
                        Pandas数据操作：其他操作
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                            <b>4.4.2.</b>
                        
                        Pandas数据存取
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                            <b>4.4.3.</b>
                        
                        Pandas数据运算
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                            <b>4.4.3.1.</b>
                        
                        Pandas数据运算-拓展
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                            <b>4.4.4.</b>
                        
                        Pandas分组聚合1
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                            <b>4.4.5.</b>
                        
                        Pandas分组聚合2
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                            <b>4.4.6.</b>
                        
                        Pandas数据规整-清理
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                            <b>4.4.7.</b>
                        
                        Pandas数据规整-转换
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                            <b>4.4.7.1.</b>
                        
                        离散化和面元划分
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                            <b>4.4.8.</b>
                        
                        Pandas数据规整-合并
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                            <b>4.5.</b>
                        
                        Pandas数据规整-重塑和轴向旋转
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                            <b>4.5.1.</b>
                        
                        透视表和交叉表
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                            <b>5.</b>
                        
                        Python可视化
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                            <b>5.1.</b>
                        
                        基础：Matplotlib常见图表
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                            <b>5.1.1.</b>
                        
                        Matplotlib常见设置和操作
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                            <b>5.2.</b>
                        
                        提升：绘图区域
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                            <b>5.3.</b>
                        
                        提升：绘图组件
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                            <b>5.4.</b>
                        
                        拓展：高级绘图
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                            <b>5.5.</b>
                        
                        拓展：数学计算展示图像
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                            <b>5.6.</b>
                        
                        拓展：注意事项
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                            <b>5.7.</b>
                        
                        拓展：pylab
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                            <b>6.</b>
                        
                        数据分析必备知识点
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                            <b>7.</b>
                        
                        数据分析流程
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                        <h1 id="matplotlib&#x7ED8;&#x56FE;&#x533A;&#x57DF;">Matplotlib-&#x7ED8;&#x56FE;&#x533A;&#x57DF;</h1>
<hr>
<pre><code class="lang-python"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
<span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt
<span class="hljs-keyword">import</span> pandas <span class="hljs-keyword">as</span> pd

<span class="hljs-comment"># plt.style.use(&apos;seaborn&apos;)</span>
plt.rcParams[<span class="hljs-string">&apos;font.family&apos;</span>] = [<span class="hljs-string">&apos;Arial Unicode MS&apos;</span>, <span class="hljs-string">&apos;Microsoft Yahei&apos;</span>, <span class="hljs-string">&apos;SimHei&apos;</span>, <span class="hljs-string">&apos;sans-serif&apos;</span>]
</code></pre>
<p>&#x7ED8;&#x56FE;&#xFF0C;&#x7B80;&#x5199;</p>
<pre><code class="lang-python">plt.plot([<span class="hljs-number">3</span>, <span class="hljs-number">9</span>, <span class="hljs-number">2</span>, <span class="hljs-number">4</span>])
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0x8b23160&gt;]
</code></pre><p><img src="images/image/output_3_1.png" alt="png"></p>
<p>&#x7B49;&#x4EF7;&#x4E8E;&#x6B63;&#x5E38;&#x5199;&#x6CD5;&#xFF0C;&#x9762;&#x5411;&#x8FC7;&#x7A0B;(&#x5E38;&#x7528;)</p>
<pre><code class="lang-python">plt.figure(<span class="hljs-number">1</span>)  <span class="hljs-comment"># &#x521B;&#x5EFA;figure&#x7236;&#x7A97;&#x53E3;&#xFF0C;&#x9ED8;&#x8BA4;&#x7F16;&#x53F7;&#x4E3A;1</span>
plt.subplot(<span class="hljs-number">111</span>)  <span class="hljs-comment"># &#x521B;&#x5EFA;ax&#x5B50;&#x7A97;&#x53E3;&#xFF0C;&#x9ED8;&#x8BA4;&#xFF1A;1&#x884C; 1&#x5217; &#x9009;&#x4E2D;&#x7B2C;1&#x4E2A;</span>
plt.plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>])
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0x8bbdef0&gt;]
</code></pre><p><img src="images/image/output_5_1.png" alt="png"></p>
<p>&#x9762;&#x5411;&#x5BF9;&#x8C61;&#x5199;&#x6CD5;&#xFF08;&#x4E86;&#x89E3;&#xFF09;&#xFF0C;&#x5C06;&#x7A97;&#x53E3;&#x5BF9;&#x8C61;&#x8D4B;&#x503C;&#x7ED9;&#x53D8;&#x91CF;</p>
<pre><code class="lang-python">fig = plt.figure(<span class="hljs-number">2</span>)  <span class="hljs-comment"># &#x521B;&#x5EFA;&#x7236;&#x5BF9;&#x8C61;</span>
ax = fig.add_subplot(<span class="hljs-number">111</span>)  <span class="hljs-comment"># &#x521B;&#x5EFA;&#x5B50;&#x5BF9;&#x8C61;</span>
ax.plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>])  <span class="hljs-comment"># &#x7ED9;&#x5B50;&#x5BF9;&#x8C61;&#x7ED8;&#x56FE;</span>
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0x62feb70&gt;]
</code></pre><p><img src="images/image/output_7_1.png" alt="png"></p>
<pre><code class="lang-python"><span class="hljs-comment"># &#x524D;&#x4E24;&#x53E5;&#x5408;&#x5E76;</span>
fig, ax = plt.subplots()
ax.plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>])
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0x63093c8&gt;]
</code></pre><p><img src="images/image/output_8_1.png" alt="png"></p>
<h2 id="&#x521B;&#x5EFA;&#x591A;&#x4E2A;figure&#x7236;&#x5BF9;&#x8C61;">&#x521B;&#x5EFA;&#x591A;&#x4E2A;figure&#x7236;&#x5BF9;&#x8C61;</h2>
<pre><code class="lang-python">plt.figure()  <span class="hljs-comment"># &#x4E0D;&#x5199;&#x7236;&#x5BF9;&#x8C61;&#x53F7;&#x7801;&#xFF0C;&#x9ED8;&#x8BA4;&#x662F;1</span>
plt.plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>])

plt.figure(
    <span class="hljs-number">2</span>,  <span class="hljs-comment"># &#x56FE;&#x50CF;&#x7F16;&#x53F7;&#xFF0C;&#x521B;&#x5EFA;&#x548C;&#x9009;&#x62E9;&#x56FE;&#x50CF;&#x4F7F;&#x7528;</span>
    figsize=(<span class="hljs-number">18</span>, <span class="hljs-number">5</span>),  <span class="hljs-comment"># &#x56FE;&#x7247;&#x5927;&#x5C0F;</span>
    facecolor=<span class="hljs-string">&apos;#cccccc&apos;</span>,  <span class="hljs-comment"># &#x80CC;&#x666F;&#x989C;&#x8272;</span>
    dpi=<span class="hljs-number">300</span>,  <span class="hljs-comment"># &#x5206;&#x8FA8;&#x7387;&#xFF0C;&#x7535;&#x8111;&#x770B;72&#xFF0C;&#x6253;&#x5370;300&#x8D77;</span>
)
plt.plot([<span class="hljs-number">2</span>,<span class="hljs-number">9</span>,<span class="hljs-number">3</span>])

plt.plot([<span class="hljs-number">3</span>,<span class="hljs-number">12</span>,<span class="hljs-number">1</span>,<span class="hljs-number">5</span>])  <span class="hljs-comment"># &#x7ED8;&#x5236;&#x5230;&#x7236;&#x5BF9;&#x8C61;2</span>

plt.figure(<span class="hljs-number">1</span>)
plt.plot([<span class="hljs-number">0</span>,<span class="hljs-number">1</span>,<span class="hljs-number">9</span>])  <span class="hljs-comment"># &#x7ED8;&#x5236;&#x5230;&#x7236;&#x5BF9;&#x8C61;1</span>
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0x63191d0&gt;]
</code></pre><p><img src="images/output_10_1.png" alt="png"></p>
<p><img src="images/output_10_2.png" alt="png"></p>
<h2 id="&#x521B;&#x5EFA;&#x591A;&#x4E2A;ax&#x5B50;&#x5BF9;&#x8C61;">&#x521B;&#x5EFA;&#x591A;&#x4E2A;ax&#x5B50;&#x5BF9;&#x8C61;</h2>
<pre><code class="lang-python"><span class="hljs-comment"># &#x7ED8;&#x5236;3&#x884C;2&#x5217;&#x5171;6&#x4E2A;&#x5B50;&#x56FE;&#xFF0C;&#x5F53;&#x524D;&#x7ED8;&#x5236;&#x7B2C;1&#x4E2A;(&#x4ECE;&#x5DE6;&#x4E0A;&#x89D2;&#x6A2A;&#x6392;&#x5F80;&#x53F3;&#x4E0B;&#x89D2;)</span>
plt.subplot(<span class="hljs-number">321</span>) <span class="hljs-comment"># &#x5982;&#x679C;&#x662F;&#x6A2A;&#x7EB5;&#x884C;&#x5217;&#x90FD;&#x662F;&#x4E2A;&#x4F4D;&#x6570;&#xFF0C;&#x53EF;&#x4EE5;&#x53BB;&#x6389;&#x9017;&#x53F7;</span>
plt.plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>])

plt.subplot(<span class="hljs-number">3</span>, <span class="hljs-number">2</span>, <span class="hljs-number">2</span>)
plt.subplot(<span class="hljs-number">3</span>, <span class="hljs-number">2</span>, <span class="hljs-number">3</span>)
plt.subplot(<span class="hljs-number">3</span>, <span class="hljs-number">2</span>, <span class="hljs-number">4</span>)
plt.subplot(<span class="hljs-number">3</span>, <span class="hljs-number">2</span>, <span class="hljs-number">5</span>)
plt.plot([<span class="hljs-number">2</span>,<span class="hljs-number">9</span>,<span class="hljs-number">1</span>])

plt.subplot(<span class="hljs-number">3</span>, <span class="hljs-number">2</span>, <span class="hljs-number">6</span>)
</code></pre>
<pre><code>&lt;matplotlib.axes._subplots.AxesSubplot at 0x9f1ecf8&gt;
</code></pre><p><img src="images/output_12_1.png" alt="png"></p>
<h2 id="fig&#x7236;&#x5BF9;&#x8C61;&#x548C;ax&#x5B50;&#x5BF9;&#x8C61;&#x7ED3;&#x5408;">fig&#x7236;&#x5BF9;&#x8C61;&#x548C;ax&#x5B50;&#x5BF9;&#x8C61;&#x7ED3;&#x5408;</h2>
<pre><code class="lang-python"><span class="hljs-comment"># &#x56FE;1</span>
plt.figure(<span class="hljs-number">1</span>)

plt.subplot(<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">1</span>)
plt.plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>])

plt.subplot(<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">2</span>)
plt.plot([<span class="hljs-number">3</span>,<span class="hljs-number">9</span>,<span class="hljs-number">1</span>])

<span class="hljs-comment"># &#x56FE;2</span>
plt.figure(<span class="hljs-number">2</span>, figsize=(<span class="hljs-number">18</span>, <span class="hljs-number">5</span>))

plt.subplot(<span class="hljs-number">1</span>,<span class="hljs-number">3</span>,<span class="hljs-number">1</span>)
plt.subplot(<span class="hljs-number">1</span>,<span class="hljs-number">3</span>,<span class="hljs-number">2</span>)
plt.subplot(<span class="hljs-number">1</span>,<span class="hljs-number">3</span>,<span class="hljs-number">3</span>)
plt.plot([<span class="hljs-number">2</span>,-<span class="hljs-number">5</span>,<span class="hljs-number">1</span>])
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0xa5f2f60&gt;]
</code></pre><p><img src="images/output_14_1.png" alt="png"></p>
<p><img src="images/output_14_2.png" alt="png"></p>
<h2 id="&#x9762;&#x5411;&#x5BF9;&#x8C61;&#x7684;fig&#x3001;ax&#x7ED3;&#x5408;&#x7684;&#x7B80;&#x5199;-&#xFF08;&#x4E86;&#x89E3;&#xFF09;">&#x9762;&#x5411;&#x5BF9;&#x8C61;&#x7684;fig&#x3001;ax&#x7ED3;&#x5408;&#x7684;&#x7B80;&#x5199; &#xFF08;&#x4E86;&#x89E3;&#xFF09;</h2>
<pre><code class="lang-python">fig, ax = plt.subplots()  <span class="hljs-comment"># &#x521B;&#x5EFA;&#x7236;&#x56FE;&#x548C;&#x5B50;&#x56FE;</span>
ax.plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>])
ax.set_title(<span class="hljs-string">&apos;&#x4F60;&#x597D;&#x518D;&#x89C1;&apos;</span>)

fig2, ax2 = plt.subplots(<span class="hljs-number">3</span>, <span class="hljs-number">2</span>)  <span class="hljs-comment"># &#x5B50;&#x56FE;&#xFF1A;3&#x884C;2&#x5217;</span>
ax2
ax2[<span class="hljs-number">1</span>, <span class="hljs-number">1</span>].plot([<span class="hljs-number">3</span>,<span class="hljs-number">1</span>,<span class="hljs-number">9</span>])  <span class="hljs-comment"># &#x7D22;&#x5F15;&#x5750;&#x6807;&#x83B7;&#x53D6;&#x5B50;&#x56FE;</span>
ax2[<span class="hljs-number">1</span>, <span class="hljs-number">1</span>].set_title(<span class="hljs-string">&apos;&#x7B2C;2&#x884C;&#x7B2C;2&#x5217;&apos;</span>)

fig3, ax3 = plt.subplots(
    figsize=(<span class="hljs-number">12</span>, <span class="hljs-number">3</span>),
    nrows=<span class="hljs-number">2</span>,
    ncols=<span class="hljs-number">3</span>,
    sharex=<span class="hljs-keyword">False</span>,
    sharey=<span class="hljs-keyword">True</span>,
)

ax3[<span class="hljs-number">0</span>,<span class="hljs-number">0</span>].plot([<span class="hljs-number">100</span>, <span class="hljs-number">200</span>, <span class="hljs-number">900</span>])
ax3[<span class="hljs-number">0</span>,<span class="hljs-number">1</span>].plot([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">9</span>])
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0xc334be0&gt;]
</code></pre><p><img src="images/output_16_1.png" alt="png"></p>
<p><img src="images/output_16_2.png" alt="png"></p>
<p><img src="images/output_16_3.png" alt="png"></p>
<hr>
<h1 id="&#x590D;&#x6742;&#x7ED8;&#x56FE;&#x533A;&#x57DF;&#xFF1A;pyplot&#x5B50;&#x7ED8;&#x56FE;&#x533A;&#x57DF;">&#x590D;&#x6742;&#x7ED8;&#x56FE;&#x533A;&#x57DF;&#xFF1A;pyplot&#x5B50;&#x7ED8;&#x56FE;&#x533A;&#x57DF;</h1>
<p>&#x8BBE;&#x5B9A;&#x7F51;&#x683C;,&#x9009;&#x4E2D;&#x7F51;&#x683C;,&#x786E;&#x5B9A;&#x9009;&#x4E2D;&#x884C;&#x5217;&#x533A;&#x57DF;&#x6570;&#x91CF;,&#x7F16;&#x53F7;&#x4ECE;0&#x5F00;&#x59CB;</p>
<p>&#x5E38;&#x7528;&#x4E8E;&#x6570;&#x636E;&#x9762;&#x677F;&#xFF0C;&#x4EEA;&#x8868;&#x677F;</p>
<pre><code class="lang-python">plt.figure(figsize=(<span class="hljs-number">18</span>, <span class="hljs-number">10</span>))

plt.subplot2grid(
    (<span class="hljs-number">4</span>, <span class="hljs-number">3</span>),  <span class="hljs-comment"># 4&#x884C;3&#x5217;</span>
    (<span class="hljs-number">0</span>, <span class="hljs-number">0</span>),  <span class="hljs-comment"># &#x9009;&#x4E2D;0&#x884C;0&#x5217;&#x5355;&#x5143;&#x683C;</span>
    colspan=<span class="hljs-number">3</span>, <span class="hljs-comment"># &#x5408;&#x5E76;3&#x5217;</span>
)
plt.plot([<span class="hljs-number">3</span>,<span class="hljs-number">5</span>,<span class="hljs-number">9</span>,<span class="hljs-number">29</span>,<span class="hljs-number">4</span>])


plt.subplot2grid(
    (<span class="hljs-number">4</span>, <span class="hljs-number">3</span>),
    (<span class="hljs-number">1</span>, <span class="hljs-number">0</span>),
    colspan=<span class="hljs-number">2</span>,
    rowspan=<span class="hljs-number">2</span>,  <span class="hljs-comment"># &#x5408;&#x5E76;2&#x884C;</span>
)
plt.bar([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>,<span class="hljs-number">5</span>],[<span class="hljs-number">3</span>,<span class="hljs-number">9</span>,<span class="hljs-number">4</span>,<span class="hljs-number">1</span>,<span class="hljs-number">8</span>])

plt.subplot2grid(
    (<span class="hljs-number">4</span>, <span class="hljs-number">3</span>),
    (<span class="hljs-number">1</span>, <span class="hljs-number">2</span>),
    rowspan=<span class="hljs-number">2</span>,   <span class="hljs-comment">#&#x5408;&#x5E76;2&#x884C;</span>
)
plt.scatter([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>,<span class="hljs-number">5</span>],[<span class="hljs-number">3</span>,<span class="hljs-number">5</span>,<span class="hljs-number">9</span>,<span class="hljs-number">4</span>,<span class="hljs-number">2</span>])

plt.subplot2grid((<span class="hljs-number">4</span>, <span class="hljs-number">3</span>),(<span class="hljs-number">3</span>, <span class="hljs-number">0</span>))
plt.pie([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>])
plt.axis(<span class="hljs-string">&apos;equal&apos;</span>)

plt.subplot2grid((<span class="hljs-number">4</span>, <span class="hljs-number">3</span>),(<span class="hljs-number">3</span>, <span class="hljs-number">1</span>))
plt.pie([<span class="hljs-number">2</span>,<span class="hljs-number">9</span>,<span class="hljs-number">1</span>,<span class="hljs-number">8</span>])
plt.axis(<span class="hljs-string">&apos;equal&apos;</span>)

plt.subplot2grid((<span class="hljs-number">4</span>, <span class="hljs-number">3</span>),(<span class="hljs-number">3</span>, <span class="hljs-number">2</span>))
plt.pie([<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">9</span>,<span class="hljs-number">8</span>,<span class="hljs-number">5</span>])
plt.axis(<span class="hljs-string">&apos;equal&apos;</span>)
</code></pre>
<pre><code>(-1.1138856103720687,
 1.1006612298966945,
 -1.1153284973014734,
 1.11725100866372)
</code></pre><p><img src="images/image/output_18_1.png" alt="png"></p>
<pre><code class="lang-python">plt.figure(figsize=(<span class="hljs-number">18</span>, <span class="hljs-number">10</span>))

plt.subplot2grid(
    (<span class="hljs-number">4</span>,<span class="hljs-number">3</span>),
    (<span class="hljs-number">3</span>,<span class="hljs-number">0</span>),
    colspan=<span class="hljs-number">1</span>,  <span class="hljs-comment">#&#x9009;&#x4E2D;&#x4E00;&#x4E2A;</span>
)
<span class="hljs-comment">#&#x9009;&#x4E2D;&#x4E86;&#x4EC0;&#x4E48;&#x90FD;&#x6CA1;&#x753B;</span>

plt.subplot2grid(
    (<span class="hljs-number">4</span>,<span class="hljs-number">3</span>),
    (<span class="hljs-number">0</span>,<span class="hljs-number">0</span>),
    colspan=<span class="hljs-number">1</span>,  <span class="hljs-comment">#&#x9009;&#x4E2D;&#x4E00;&#x4E2A;</span>
)
plt.pie([<span class="hljs-number">45</span>,<span class="hljs-number">55</span>])
plt.axis(<span class="hljs-string">&apos;equal&apos;</span>)

plt.subplot2grid(
    (<span class="hljs-number">4</span>,<span class="hljs-number">3</span>),
    (<span class="hljs-number">0</span>,<span class="hljs-number">1</span>),
    colspan=<span class="hljs-number">2</span>,  <span class="hljs-comment">#&#x5408;&#x5E76;2&#x5217;</span>
)

plt.subplot2grid(
    (<span class="hljs-number">4</span>,<span class="hljs-number">3</span>),
    (<span class="hljs-number">1</span>,<span class="hljs-number">0</span>),
    rowspan=<span class="hljs-number">2</span>,  <span class="hljs-comment">#&#x5408;&#x5E76;2&#x884C;</span>
    colspan=<span class="hljs-number">3</span>,   <span class="hljs-comment">#&#x5408;&#x5E76;3&#x5217;</span>
)
</code></pre>
<pre><code>&lt;matplotlib.axes._subplots.AxesSubplot at 0xdd12278&gt;
</code></pre><p><img src="images/image/output_19_1.png" alt="png"></p>

                    
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